{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Weyers BW"],"funding":["NCI NIH HHS","National Institutes of Health","NIH HHS"],"pagination":["1765-1776"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9979707"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["44(8)"],"pubmed_abstract":["<h4>Background</h4>This study evaluated whether fluorescence lifetime imaging (FLIm), coupled with standard diagnostic workups, could enhance primary lesion detection in patients with p16+ head and neck squamous cell carcinoma of the unknown primary (HNSCCUP).<h4>Methods</h4>FLIm was integrated into transoral robotic surgery to acquire optical data on six HNSCCUP patients' oropharyngeal tissues. An additional 55-patient FLIm dataset, comprising conventional primary tumors, trained a machine learning classifier; the output predicted the presence and location of HNSCCUP for the six patients. Validation was performed using histopathology.<h4>Results</h4>Among the six HNSCCUP patients, p16+ occult primary was surgically identified in three patients, whereas three patients ultimately had no ide"],"journal":["Head & neck"],"pubmed_title":["Intraoperative delineation of p16+ oropharyngeal carcinoma of unknown primary origin with fluorescence lifetime imaging: Preliminary report."],"pmcid":["PMC9979707"],"funding_grant_id":["R01 CA187427","P30 CA093373"],"pubmed_authors":["Birkeland AC","Gui D","Marsden MA","Weyers BW","Farwell DG","Frusciante RP","Marcu L","Bewley AF","Bec J","Tam A","Abouyared M"],"additional_accession":[]},"is_claimable":false,"name":"Intraoperative delineation of p16+ oropharyngeal carcinoma of unknown primary origin with fluorescence lifetime imaging: Preliminary report.","description":"<h4>Background</h4>This study evaluated whether fluorescence lifetime imaging (FLIm), coupled with standard diagnostic workups, could enhance primary lesion detection in patients with p16+ head and neck squamous cell carcinoma of the unknown primary (HNSCCUP).<h4>Methods</h4>FLIm was integrated into transoral robotic surgery to acquire optical data on six HNSCCUP patients' oropharyngeal tissues. An additional 55-patient FLIm dataset, comprising conventional primary tumors, trained a machine learning classifier; the output predicted the presence and location of HNSCCUP for the six patients. Validation was performed using histopathology.<h4>Results</h4>Among the six HNSCCUP patients, p16+ occult primary was surgically identified in three patients, whereas three patients ultimately had no ide","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Aug","modification":"2025-04-04T20:04:08.45Z","creation":"2025-04-04T20:04:08.45Z"},"accession":"S-EPMC9979707","cross_references":{"pubmed":["35511208"],"doi":["10.1002/hed.27078"]}}